Navigating the cohesion-diversity trade-off: understanding the role of facilitators in co-creation using agent-based modelling.

In the domain of participatory research and co-creation, understanding the dynamic interplay between group cohesion and diversity is pivotal for fostering innovation. While diversity fuels the generation of novel ideas, cohesion ensures these ideas are effectively synthesized and implemented. This study aims to explore the nuanced role that facilitators play in navigating the balance between cohesion and diversity, particularly in groups characterized by pronounced faultlines.

Co-creating the future: participatory cities and digital governance.

The digital revolution, fuelled by advancements in social media, Big Data, the Internet of Things and Artificial Intelligence, is reshaping our urban landscapes into 'participatory cities'. These cities leverage digital technologies to foster citizen engagement, collaborative decision-making and community-driven urban development, thus unlocking new potentials while confronting emerging threats. Such technologies are empowering individuals and organizations in ways that were unimaginable just a few years ago.

Global comparison of urban bike-sharing accessibility across 40 cities.

The global expansion of bike-sharing networks offers a cost-effective and environmentally friendly transportation alternative that complements public transit and promotes active, healthy lifestyles. Despite significant research, most studies focus on individual locations, specific environmental or health impacts, or infrastructure elements like bike lanes. Instead, this paper elaborates a comprehensive global comparison of bike-sharing systems by introducing a novel database that aggregates data from 40 cities worldwide.

A virtual reality experiment to study pedestrian perception of future street scenarios.

The current allocation of street space is based on expected vehicular peak-hour flows. Flexible and adaptive use of this space can respond to changing needs. To evaluate the acceptability of flexible street layouts, several urban environments were designed and implemented in virtual reality.

Design and development of an open-source framework for citizen-centric environmental monitoring and data analysis.

Cities around the world are struggling with environmental pollution. The conventional monitoring approaches are not effective for undertaking large-scale environmental monitoring due to logistical and cost-related issues. The availability of low-cost and low-power Internet of Things (IoT) devices has proved to be an effective alternative to monitoring the environment.

: An Open-Source Toolbox for Visualization and Analysis of Crowd-Sourced Sensor Data.

Recent advances in sensor technology and the availability of low-cost and low-power sensors have changed the air quality monitoring paradigm. These sensors are being widely used by scientists and citizens for monitoring air quality at finer spatial-temporal resolution. Such practices are opening up opportunities to enhance the traditional monitoring networks, but at the same time, these sensors are producing large data sets that can become overwhelming and challenging when it comes to the scientific tools and skills required to analyze the data.

: A Citizen-Sensing Toolkit for Monitoring Air Quality.

Increasing urbanisation and a better understanding of the negative health effects of air pollution have accelerated the use of Internet of Things (IoT)-based air quality sensors. Low-cost and low-power sensors are now readily available and commonly deployed by individuals and community groups. However, there are a wide range of such IoT devices in circulation that differently focus on problems of sensor validation, data reliability, or accessibility.

Short-Term PM2.5 Forecasting Using Exponential Smoothing Method: A Comparative Analysis.

Air pollution is a global problem and can be perceived as a modern-day curse. One way of dealing with it is by finding economical ways to monitor and forecast air quality. Accurately monitoring and forecasting fine particulate matter (PM2.